UTILIZING MACHINE LEARNING AND IMAGE PROCESSING TO DETECT SIGNS OF STRESS IN INDIVIDUALS

Main Article Content

SRIKANTH REDDY KONNI
KHAJA ZIAUDDIN

Abstract

This study's main objective is to identify stress in the human body using vivid machine learning and image processing techniques. Our system is an improved version of earlier stress detection systems that lacked personal counseling or live detection. Instead, it detects employees' levels of both physical and mental stress and offers appropriate stress management strategies through a survey form. Additionally, our system includes periodic analysis of employees and live detection. To make the most of employees during working hours, our approach is mainly concerned with stress management and fostering a positive, flexible work environment.

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How to Cite
KONNI, S. R. ., & ZIAUDDIN, K. . (2020). UTILIZING MACHINE LEARNING AND IMAGE PROCESSING TO DETECT SIGNS OF STRESS IN INDIVIDUALS. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 11(3), 2838–2848. https://doi.org/10.61841/turcomat.v11i3.14588
Section
Research Articles

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